<b>The Mass-Energy Gravity (MEG) Model: A Viable Alternative to ΛCDM Without Dark Energy</b>

This paper introduces the Mass-Energy Gravity (MEG) Model, a novel approach to cosmic expansion that eliminates the need for dark energy. MEG proposes that cosmic expansion itself generates energy-density gradients (EDGs), which in turn shape gravitational dynamics and structure formation. Unlike ΛCDM, which relies on a cosmological constant (Λ) to drive acceleration, MEG explains the observational effects of acceleration as a consequence of differential expansion across cosmic structures, without invoking an external repulsive force.We present the latest refinements of the MEG model, showing that it now:<br>Accurately fits supernova, BAO, and CMB constraints without requiring dark energy.<br>Improves predictions at high-redshift (z&gt;2.5z&gt;2.5), outperforming ΛCDM in JWST/DESI datasets.<br>Predicts alternative observational signatures, including subtle differences in gravitational lensing and cosmic void distributions.A detailed statistical comparison with ΛCDM, including chi-squared analysis, Bayesian likelihood estimation, and Akaike Information Criterion (AIC), demonstrates that while ΛCDM remains preferred due to its simplicity, MEG provides a physically motivated alternative with competitive predictive power.This study suggests that the apparent cosmic acceleration is not fundamental, but rather an observational effect of differential expansion rates driven by energy-density variations. This challenges the necessity of dark energy and opens new avenues for understanding cosmic evolution under an energy-density-based framework.<i>For inquiries, please contact me at:</i> <b>[email protected]</b><br><br>

Publication Details

Journal
OPAL (Open@LaTrobe) (La Trobe University)
Published
2025-01-01
DOI
https://doi.org/10.6084/m9.figshare.28504496.v7
Primary Topic
Genetic and Environmental Crop Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Mass-Energy Gravity (MEG) Model: A Viable Alternative to ΛCDM Without Dark Energy

OPAL (Open@LaTrobe) (La Trobe University)
Genetic and Environmental Crop Studies
article

The Mass-Energy Gravity (MEG) Model: A Viable Alternative to ΛCDM Without Dark Energy

article en

Abstract

This paper introduces the Mass-Energy Gravity (MEG) Model, a novel approach to cosmic expansion that eliminates the need for dark energy. MEG proposes that cosmic expansion itself generates energy-density gradients (EDGs), which in turn shape gravitational dynamics and structure formation. Unlike ΛCDM, which relies on a cosmological constant (Λ) to drive acceleration, MEG explains the observational effects of acceleration as a consequence of differential expansion across cosmic structures, without invoking an external repulsive force.We present the latest refinements of the MEG model, showing that it now:<br>Accurately fits supernova, BAO, and CMB constraints without requiring dark energy.<br>Improves predictions at high-redshift (z&gt;2.5z&gt;2.5), outperforming ΛCDM in JWST/DESI datasets.<br>Predicts alternative observational signatures, including subtle differences in gravitational lensing and cosmic void distributions.A detailed statistical comparison with ΛCDM, including chi-squared analysis, Bayesian likelihood estimation, and Akaike Information Criterion (AIC), demonstrates that while ΛCDM remains preferred due to its simplicity, MEG provides a physically motivated alternative with competitive predictive power.This study suggests that the apparent cosmic acceleration is not fundamental, but rather an observational effect of differential expansion rates driven by energy-density variations. This challenges the necessity of dark energy and opens new avenues for understanding cosmic evolution under an energy-density-based framework.<i>For inquiries, please contact me at:</i> <b>[email protected]</b><br><br>

OPAL (Open@LaTrobe) (La Trobe University)
Affordable and clean energy
Openalex Percentile: Top 43%
Genetic and Environmental Crop Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

<b>The Mass-Energy Gravity (MEG) Model: A Viable Alternative to ΛCDM Without Dark Energy</b> · OPAL (Open@LaTrobe) (La Trobe University) (2025) | TGRS Research Map | TGRS